Abstract-With virtual machine (VM) technology being increasingly mature, computing resources in modern Cloud systems can be partitioned in fine granularity and allocated on demand with "pay-as-you-go" model. In this work, we study the resource query and allocation problems in a SelfOrganizing Cloud (SOC), where host machines are connected by a peer-to-peer (P2P) overlay network on the Internet. To run a user task in SOC, the requester needs to perform a multi-dimensional range search over the P2P network for locating host machines that satisfy its minimal demand on each type of resources. The multi-dimensional range search problem is known to be challenging as contentions along multiple dimensions could happen in the presence of the uncoordinated analogous queries. Moreover, low resource matching rate may happen while restricting query delay and network traffic. We design a novel resource discovery protocol, namely Proactive Index Diffusion CAN (PID-CAN), which can proactively diffuse resource indexes over the nodes and randomly route query messages among them. Such a protocol is especially suitable for the range query that needs to maximize its best-fit resource shares under possible competition along multiple resource dimensions. Via simulation, we show that PID-CAN could keep stable and optimized searching performance with low query delay and traffic overhead, for various test cases under different distributions of query ranges and competition degrees. It also performs satisfactorily in dynamic node-churning situation.

No abstract

Abstract-With the increasing scale of applications and the number of users, we design a Self-organizing Cloud (SoC) which aims to make use of the distributed volunteer computers or dedicated machines to provide powerful computing ability. These resources are provisioned elastically according to user's specific demand, by leveraging virtual machine (VM) resource isolation technology. Based on such a framework, we propose a social-optimized auction-based resource allocation scheme, which mainly tackles two issues: (1) how to make full use of the widely dispersed multi-attribute idle resources to construct a win-win situation, such that each task schedule could let both sides (resource providers and consumers) be satisfied with their final payoffs. (2) The total resource utility welfare should also be optimized to guarantee the overall performance around the global system. The key challenge of getting the win-win effect with social optimization is its provable NP-completeness. Finally, we validate that our approach can effectively improve the resource contributor's payoffs up to about five times as the level without our method via simulation work. Meanwhile, our approach can also keep a high level of the processing rate for the task scheduling.

Abstract-A Virtual Private Cloud (VPC) is a secure collection of computing, storage and network resources spanning multiple sites over Wide Area Network (WAN). With VPC, computation and services are no longer restricted to a fixed site but can be relocated dynamically across geographical sites to improve manageability, performance and fault tolerance. We propose WAVNet, a layer 2 virtual private network (VPN) which supports virtual machine live migration over WAN to realize mobility of execution environment across multiple security domains. WAVNet adopts a UDP hole punching technique to achieve direct network connection between two Internet hosts without special router configuration. We evaluate our design in an emulated WAN with 64 hosts and also in a real WAN environment with 10 machines located at seven different sites across the Asia-Pacific region. The experimental results show that WAVNet not only achieves close-to-native host-tohost network bandwidth and latency, but also guarantees more effective VM live migration than existing solutions.

Abstract-While modern datacenters are increasingly adopting virtual machines (VMs) to provide elastic cloud services, they still rely on traditional TCP for congestion control. In virtualized datacenters, TCP endpoints are separated by a virtualization layer and subject to the intervention of the hypervisor's scheduling. Most previous attempts focused on tuning the hypervisor layer to try to improve the VMs' I/O performance, and there is very little work on how a VM's guest OS may help the transport layer to adapt to the virtualized environment. In this paper, we find that VM scheduling delays can heavily contaminate RTTs as sensed by VM senders, preventing TCP from correctly learning the physical network condition. After giving an account of the source of the problem, we propose PVTCP, a ParaVirtualized TCP to counter the distorted congestion information caused by VM scheduling on the sender side. PVTCP is self-contained, requiring no modification to the hypervisor. Experiments show that PVTCP is much more effective in addressing incast congestion in virtualized datacenters than standard TCP.